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While many optimization problems, such as optimizing revenue [1], can be NP-hard requiring heuristic solutions, they do not address the performance requirements of individual user applications.
Many optimization problems in engineering and science require solutions that are globally optimal.
The motivation behind this reformulation comes from the fact that for many optimization problems we cannot evaluate exactly the objective function to be optimized.
Many optimization problems of practical interest are computationally intractable.
Many optimization problems can be phrased in terms of constraint satisfaction.
We previously applied it to many optimization problems including protein structure prediction and graph community detection.
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The proposed algorithm is efficient, robust and applicable to many optimization problem for composite plates.
Swarm intelligence techniques have been successfully applied in solving many combinatorial optimization problems in which the objective space possesses many local optimal solutions.
As mentioned in Section 1, the (EP) contains many optimization related problems as special cases.
Many engineering optimization problems involve decision variables of continuous nature.
Many industrial optimization problems can be translated to MaxSAT.
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